Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally.

Using data available up to the: 2020-04-03

Expected daily cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated cases with a date of infection on the 2020-03-24) can be summarised by whether cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 100 cases reported on a single day are not included in the analysis (light grey).

Summary of latest reproduction number and case count estimates by date of infection


Figure 1: Cases with date of infection on the 2020-03-24 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily cases and shaded based on the expected change in daily cases. The dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most incident cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of incident cases. Estimates are shown up to the 2020-03-24. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.

Reported cases and their estimated date of infection in the six regions expected to have the most incident cases


Figure 3: Cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of incident cases. Estimates are shown up to the 2020-03-24. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-03-24. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.

Reported cases and their estimated date of infection in all regions

Figure 5: Cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-03-24. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Latest estimates (as of the 2020-03-24)

Table 1: Latest estimates (as of the 2020-03-24) of the number of cases by date of infection, the effective reproduction number, and the doubling time in each region. The mean and 90% credible interval is shown.
Country/Region New cases by infection date Expected change in daily cases Effective reproduction no. Doubling time (days)
Algeria 160 (34 – 258) Increasing 1.9 (0.8 – 2.7) 5.8 (2.7 – Inf)
Argentina 130 (32 – 214) Likely increasing 1.3 (0.8 – 1.8) 18 (4.9 – Inf)
Australia 337 (192 – 469) Unsure 1 (0.7 – 1.3) -45 (16 – Inf)
Austria 737 (386 – 1075) Unsure 1 (0.7 – 1.3) -67 (15 – Inf)
Belgium 1487 (840 – 2182) Likely increasing 1.3 (0.8 – 1.7) 13 (4.9 – Inf)
Brazil 991 (439 – 1577) Likely increasing 1.6 (0.9 – 2.2) 7.6 (3.7 – Inf)
Canada 1222 (683 – 1749) Likely increasing 1.4 (0.9 – 1.8) 12 (5.5 – Inf)
Chile 363 (184 – 569) Likely increasing 1.4 (0.9 – 1.9) 12 (5 – Inf)
China 92 (52 – 126) Unsure 1 (0.7 – 1.2) -83 (14 – Inf)
Colombia 158 (59 – 255) Likely increasing 1.6 (0.9 – 2.3) 7.8 (3.5 – Inf)
Czech Republic 308 (156 – 456) Unsure 1.1 (0.8 – 1.5) 27 (7.1 – Inf)
Denmark 278 (132 – 405) Likely increasing 1.4 (0.9 – 1.9) 9.5 (4.6 – Inf)
Dominican Republic 224 (56 – 373) Likely increasing 1.6 (0.8 – 2.3) 7.9 (3.4 – Inf)
Ecuador 331 (110 – 537) Likely increasing 1.4 (0.8 – 2.1) 11 (4.2 – Inf)
Estonia 49 (19 – 80) Unsure 1 (0.6 – 1.4) -120 (7.3 – Inf)
Finland 89 (31 – 135) Unsure 1 (0.7 – 1.4) -130 (8.2 – Inf)
France 5932 (3176 – 8545) Likely increasing 1.4 (0.9 – 1.7) 12 (5.4 – Inf)
Germany 6063 (3266 – 8390) Unsure 1.1 (0.9 – 1.5) 25 (8.2 – Inf)
Greece 97 (39 – 140) Unsure 1.2 (0.7 – 1.6) 28 (6.5 – Inf)
India 319 (124 – 520) Increasing 1.8 (1 – 2.5) 5.9 (3 – 88)
Indonesia 177 (59 – 277) Likely increasing 1.3 (0.8 – 1.8) 15 (5 – Inf)
Iran 3557 (2177 – 5080) Likely increasing 1.3 (0.9 – 1.7) 14 (6 – Inf)
Ireland 335 (137 – 483) Likely increasing 1.2 (0.8 – 1.6) 21 (6.3 – Inf)
Israel 614 (319 – 917) Likely increasing 1.3 (0.9 – 1.7) 16 (6.2 – Inf)
Italy 5340 (3343 – 7666) Unsure 1 (0.8 – 1.3) -100 (14 – Inf)
Japan 138 (67 – 193) Likely increasing 1.3 (0.9 – 1.6) 16 (6 – Inf)
Luxembourg 180 (71 – 273) Unsure 1.1 (0.7 – 1.4) -1300 (8.9 – Inf)
Malaysia 176 (80 – 265) Unsure 1 (0.7 – 1.3) 25000 (10 – Inf)
Mexico 177 (77 – 266) Likely increasing 1.4 (0.9 – 1.9) 9.8 (4.2 – Inf)
Morocco 92 (36 – 157) Likely increasing 1.4 (0.8 – 2) 11 (3.9 – Inf)
Netherlands 1166 (644 – 1658) Unsure 1.1 (0.8 – 1.5) 26 (7.5 – Inf)
Norway 247 (125 – 353) Unsure 1 (0.7 – 1.2) -43 (14 – Inf)
Pakistan 336 (100 – 546) Likely increasing 1.7 (0.8 – 2.6) 6.3 (3 – Inf)
Panama 155 (61 – 245) Likely increasing 1.3 (0.8 – 1.8) 17 (5.6 – Inf)
Peru 208 (74 – 338) Increasing 1.7 (0.9 – 2.5) 6.1 (3 – Inf)
Philippines 378 (112 – 620) Likely increasing 1.7 (0.8 – 2.5) 6.4 (2.8 – Inf)
Poland 303 (150 – 472) Likely increasing 1.4 (0.9 – 1.9) 11 (4.6 – Inf)
Portugal 988 (512 – 1525) Likely increasing 1.3 (0.9 – 1.8) 12 (5.2 – Inf)
Qatar 82 (31 – 132) Increasing 2 (1 – 2.9) 4.9 (2.6 – 41)
Romania 304 (142 – 459) Likely increasing 1.4 (0.9 – 1.8) 12 (4.9 – Inf)
Russia 516 (210 – 843) Increasing 1.8 (1 – 2.6) 5.8 (3 – 69)
Saudi Arabia 180 (55 – 294) Likely increasing 1.3 (0.7 – 1.8) 21 (5.2 – Inf)
Serbia 158 (53 – 255) Likely increasing 1.5 (0.9 – 2.1) 8.1 (3.5 – Inf)
Singapore 60 (24 – 90) Unsure 1.1 (0.8 – 1.5) 33 (6.5 – Inf)
South Africa 58 (16 – 92) Decreasing 0.6 (0.3 – 0.8) -5.5 (Inf – Inf)
South Korea 115 (59 – 171) Unsure 1.1 (0.7 – 1.3) 62 (8.8 – Inf)
Spain 8997 (4884 – 12610) Unsure 1.1 (0.8 – 1.5) 28 (8.4 – Inf)
Sweden 465 (256 – 689) Likely increasing 1.4 (0.9 – 1.8) 11 (5.2 – Inf)
Switzerland 1160 (581 – 1619) Unsure 1.1 (0.8 – 1.4) 60 (9.4 – Inf)
Thailand 153 (60 – 234) Unsure 1.3 (0.8 – 1.8) 17 (5 – Inf)
Turkey 2975 (1221 – 5029) Likely increasing 1.6 (0.9 – 2.3) 6.6 (3.3 – Inf)
Ukraine 195 (42 – 338) Increasing 2 (0.9 – 3) 4.8 (2.4 – 1300)
United Arab Emirates 90 (29 – 149) Likely increasing 1.5 (0.8 – 2.1) 9.6 (3.7 – Inf)
United Kingdom 3731 (2051 – 5367) Likely increasing 1.4 (0.9 – 1.8) 9.3 (4.8 – 170)
United States of America 26659 (15125 – 36534) Likely increasing 1.4 (1 – 1.8) 11 (5.4 – 250)